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Optimal Non-Asymptotic Lower Bound on the Minimax Regret of Learning with Expert Advice (1511.02176v1)

Published 6 Nov 2015 in stat.ML and cs.LG

Abstract: We prove non-asymptotic lower bounds on the expectation of the maximum of $d$ independent Gaussian variables and the expectation of the maximum of $d$ independent symmetric random walks. Both lower bounds recover the optimal leading constant in the limit. A simple application of the lower bound for random walks is an (asymptotically optimal) non-asymptotic lower bound on the minimax regret of online learning with expert advice.

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